A gyro is an inertial measurement device capable of measuring a rotation angular velocity of a motion carrier relative to an inertial space, and measurement precision of the angular velocity is a key parameter representing performance level of the gyro. An angle is an integration of angular velocity, and an error of the angle measurement increases with the increase of integration time, which is a common problem of all inertial measurement devices including gyros. A star sensor (hereinafter referred to as: SS) is a device for the navigation-positioning of a motion carrier through fixed stars, and it is particularly adaptive to the attitude measurement of the motion carrier. The main characteristic of the star sensor is that the measurement precision does not vary with time. However, there is a large dynamic influence from the motion carrier, particularly the rotation motion of the motion carrier. The higher the rotation angular velocity of the motion carrier is, the severer blurring the image of measured fixed star on the star sensor has, and in turn the measurement precision becomes poorer and is far deteriorated from that when the star sensor is stationary. Therefore, how to maintain high-precision attitude measurement of the star sensor under highly dynamic environment is a difficulty urgently to be solved in the navigation positioning.
A paper “A Novel Approach Based on MEMS-Gyro's Data Deep Coupling for Determining the Centroid of Star point” published in Mathematical Problems in Engineering in August 2012 introduces a method of real-timely measuring an angular velocity in the exposure time of a star sensor with three MEMS gyros, calculating lengths and directions of star points in an image plane of the star sensor according to the angular velocity, determining a window size of a centroid extraction algorithm of the star points, and extracting centric coordinates of the star points with the centroid extraction algorithm. The method establishes, based on Extended Kalman Filter (EKF) algorithm, an EKF equation that merges the real-timely measured angular velocities of the gyros and the centroid extraction algorithm of the star points, and obtains optimal estimations of the coordinates of the star points in a single measurement given by the star sensor under dynamic conditions. As for the dynamic condition of 8°/s of the five-magnitude star, the extraction precision is below one pixel.
In order to resolve nonlinear problem of state equation in a satellite attitude determination system, a Chinese patent publication, titled “high-precision satellite attitude determination method based on star sensor and gyro” (publication number: CN201010194288.2) proposes a filtering method based on non-linear prediction to estimate a model error, which performs an optimal state estimation using an interpolation filtering after compensating for the state equation, so as to obtain the satellite attitude. The patent document does not relate to the processing of dynamic images of the star sensor.
A paper “Dynamical Binning for High Angular Rate Star Tracking” published in Proceedings of the Fourth ESA International Conference on Spacecraft Guidance, Navigation and Control Systems, Netherlands, 1999 introduces a dynamic binning method combined with Active Pixel Sensor (APS) technique, in which the angular velocity of a star sensor is measured in real time through a gyro, and movement of pixels in the APS-CCD is synchronously controlled to eliminate dynamic influence. Although the method may achieve higher precision under higher dynamic conditions when it is used in a satellite, the influence from the rotation angular velocity around the optical axis of the star sensor cannot be eliminated.
A paper “Blurred Star Image Processing for Star Sensors under Dynamic Conditions” published in Sensors (Issue 12, 2012) introduces a method of restoring the motion-blurred image according to an angular velocity obtained from adjacent frames. In the method, firstly a Fourier transform is applied to a star image frame of the star sensor so as to convert to the frequency domain. Then deconvolution is made in the frequency domain by using Wiener filtering according to the angular velocity. Finally, an inverse Fourier transform is implemented so as to convert to a spatial domain. Therefore, the influences from the dynamic trailing and the dynamic blurring of the star image may be better solved, and the recovered star points may reach sub-pixel precision. However, the method predicts motion parameters using information of adjacent frames, and the error is large under high dynamic conditions, which leads to great difference between the original star image obtained from the deconvolution and the static star image. In addition, only a single-frame star image is processed in the attitude determination and the number of effective fixed stars is limited in the field of view of the single-frame star image, which statistically restricted its precision improvement.
The Chinese patent application, titled “star tracking method of star sensor under high dynamic state” (application number: CN200810209622. X) proposes to extract corresponding star image coordinates from a star image of the current frame according to ideal star image coordinate information predicted from a previous frame of the star sensor, and calculates attitude information of the current frame of the star sensor by using the star image coordinates extracted from the current frame and celestial coordinates corresponding to the star images. Thus it provides a tracking algorithm for extracting actual star image positions with reference to an ideal star image center predicted from the previous frame. The Chinese patent application, titled “method for restoring fixed star image under high dynamic” (Application Number: CN201310053071.3) proposes to predict the attitude of the current frame according to attitude information of the previous two frames, on the basis of the mobile quaternion information of the attitudes of star images for the previous two frames. The mobile quaternion is used to recover the fixed star image of the current frame, thereby extracting the star image coordinates for an attitude calculation. The essence of both is to predict and process the current image frame according to the angular velocity obtained from the attitudes of the previous two frames measured by the star sensor when there is no gyro, and the difference only lies in the specific methods. Since the dynamic conditions have a significant influence on the attitude measurement precision of the star sensor, the errors of the angular velocities obtained by the two methods are very large, and the effect of the dynamic compensation based on such angular velocities is poor. Meanwhile, both methods use the star image information of a single-frame star image in the attitude calculation, without extending the field of view or increasing the number of effective star points in the view filed, thus the attitude precision is restricted by the limited number of fixed stars in the single-frame star image.
By compensating for the dynamic image frame of the star sensor based on the angular velocity measured by the gyro, the influence of the angular motion on the extraction of the star point coordinates may be effectively reduced. Thus, the measurement precision of the star sensor under dynamic conditions is improved. However, due to the joint influences from the noise, exposure time of the star sensor and deconvolution, etc., the extraction precision of the star sensor coordinates is poorer than that of static conditions, and may not meet the requirement of high-precision measurement under dynamic conditions.